Knicks vs Milwaukee Bucks Match Player Stats
The knicks vs milwaukee bucks match player stats from November 29, 2025, show how the New York Knicks earned a 118-109 victory over the Milwaukee Bucks in NBA Cup Group Play at Madison Square Garden. Jalen Brunson led New York with 37 points, while Josh Hart recorded 19 points, 15 rebounds, and seven assists. For Milwaukee, Giannis Antetokounmpo delivered 30 points, 15 rebounds, and eight assists, but his outstanding all-around performance was not enough to secure the win.
The result was shaped by more than individual scoring. Milwaukee shot 52% from the field and made 18 three-pointers, both better figures than New York recorded. However, the Knicks finished with nine more total rebounds, 11 more made free throws, and three fewer turnovers. Those advantages helped New York overcome the Bucks’ superior shooting percentages and finish with a nine-point victory.
This detailed game analysis examines the final score, individual player performances, team statistics, quarter-by-quarter scoring, and the factors that separated the two teams. It also explains how to interpret the numbers accurately, so readers can understand not just who scored the most points, but how the game developed and why the final result favored New York.
Game Overview: New York Knicks vs. Milwaukee Bucks
The November 29 matchup took place at Madison Square Garden in New York, with a reported attendance of 19,812. It was an NBA Cup Group Play contest, featuring two teams with different strengths on offense.
New York entered the game with a listed record of 12-6 overall and 9-1 at home. Milwaukee’s displayed record was 8-12 overall and 3-6 on the road. These records provide context for the matchup, although they should be understood as the figures recorded in the supplied game data rather than current standings.
New York Knicks
Home
118
FINAL
118-109
9-point margin
Milwaukee Bucks
Away
109
Date
November 29, 2025
Competition
NBA Cup Group Play
Venue
Madison Square Garden
Attendance
19,812
The final score tells us who won, but the team statistics explain the result more clearly. Milwaukee made more field goals per attempt and converted more three-pointers. New York compensated by collecting additional rebounds, getting to the free-throw line more often, and protecting possession more effectively.
That contrast makes this game particularly useful for understanding basketball statistics. A team can shoot more efficiently and still lose when its opponent generates more scoring opportunities through other parts of the game.
Knicks vs Milwaukee Bucks Match Player Stats: Complete Team Box Score
The following table compares the main statistical categories recorded for both teams. These figures form the foundation for understanding the individual performances and the factors behind New York’s victory.
| Team statistic | New York Knicks | Milwaukee Bucks |
| Points | 118 | 109 |
| Field goals made/attempted | 38/84 | 37/71 |
| Field-goal percentage | 45% | 52% |
| Three-pointers made/attempted | 14/34 | 18/41 |
| Three-point percentage | 41% | 44% |
| Free throws made/attempted | 28/33 | 17/25 |
| Free-throw percentage | 85% | 68% |
| Total rebounds | 44 | 35 |
| Offensive rebounds | 14 | 5 |
| Defensive rebounds | 30 | 30 |
| Assists | 25 | 24 |
| Turnovers | 12 | 15 |
| Steals | 10 | 9 |
| Blocks | 2 | 4 |
| Personal fouls | 21 | 26 |
Source: Supplied ESPN game data. Percentages are reported as supplied and rounded to whole numbers.
Four areas stand out from this comparison.
First, Milwaukee’s shooting efficiency was better. The Bucks made 52% of their field-goal attempts, compared with 45% for New York, and connected on four more three-pointers.
Second, New York won the rebounding battle by nine. The most significant difference came on the offensive glass, where the Knicks collected 14 rebounds to Milwaukee’s five.
Third, New York made 11 more free throws. The Knicks converted 28 attempts, while the Bucks made 17.
Finally, Milwaukee committed three more turnovers. Although that difference was relatively small, it favored New York in a game decided by nine points.
Taken together, these figures reveal that the Knicks’ victory was built on several complementary advantages rather than one overwhelming statistical category.
Quarter-by-Quarter Scoring Breakdown
The scoring pattern reveals how New York recovered from Milwaukee’s strong start and built an advantage over the remaining three quarters.
| Quarter | New York Knicks | Milwaukee Bucks | Quarter winner |
| First | 33 | 37 | Milwaukee |
| Second | 28 | 25 | New York |
| Third | 31 | 26 | New York |
| Fourth | 26 | 21 | New York |
| Total | 118 | 109 | New York |
First quarter: Milwaukee starts aggressively
Milwaukee scored 37 points in the opening quarter, four more than New York’s 33. That start showed the Bucks’ ability to generate offense quickly, particularly through their efficient shooting.
New York remained close despite allowing 37 points. A four-point deficit after one quarter is manageable, but it creates pressure to respond without rushing possessions or abandoning the original game plan.
The Knicks did not need to win the opening quarter to win the game. Their ability to remain within reach gave them an opportunity to make up the difference over the following periods.
Second quarter: The Knicks respond
New York outscored Milwaukee 28-25 in the second quarter. The three-point advantage reduced the gap created in the opening period.
By halftime, Milwaukee’s early lead had narrowed from four points to one. The scoring sequence is important because it shows that New York began recovering ground before the second half.
A close halftime score also meant neither team could rely on the opening quarter as a reliable predictor of the final result.
Third quarter: New York takes control
The Knicks won the third quarter 31-26, adding another five points to their advantage over that period.
This was a significant stage of the game because New York moved beyond simply recovering from its early deficit. The team began building a lead through sustained scoring.
Milwaukee continued to score, but its 26 points were not enough to match New York’s 31. The five-point difference gave the Knicks a stronger position heading into the final quarter.
Fourth quarter: The Knicks maintain their advantage
New York outscored Milwaukee 26-21 in the fourth quarter. Both teams scored fewer points than they had in the opening period, but the Knicks maintained the better scoring rate.
The five-point fourth-quarter margin extended New York’s advantage and produced the final nine-point victory.
The supplied quarter totals do not establish which specific possessions decided the closing minutes. They do show that New York won every quarter after the first, which is a stronger explanation of the overall scoring pattern than focusing only on the final period.
What the quarter scores tell us
The Knicks scored 85 points across the second, third, and fourth quarters, while Milwaukee scored 72 during those same periods.
That 13-point difference erased Milwaukee’s four-point opening-quarter advantage and left New York ahead by nine.
The key takeaway is that the Knicks responded consistently. They did not rely on a single scoring burst to recover from the opening deficit. Instead, they produced a positive scoring margin in each of the final three quarters.
Jalen Brunson’s 37 Points Lead New York
Jalen Brunson was the Knicks’ leading scorer and the highest-scoring player in the supplied box score. His 37 points gave New York a dependable source of offense in a game where Milwaukee shot efficiently.
| Jalen Brunson’s recorded statistics | Total |
| Points | 37 |
| Rebounds | 1 |
| Assists | 5 |
Brunson’s scoring total was seven points higher than Giannis Antetokounmpo’s 30. That difference did not decide the game by itself, but it established Brunson as New York’s most productive scorer.
Why Brunson’s scoring was important
A reliable scoring option: Milwaukee made 37 field goals and 18 three-pointers. The Knicks needed to answer that offensive production, and Brunson’s 37 points gave them a major source of scoring.
Support from teammates: Brunson was not New York’s only productive scorer. Hart and McBride each recorded 19 points, while Bridges added 14. That distribution reduced the risk of the entire offense depending on one player.
Contribution to the overall result: The Knicks finished with 118 points and won by nine. Brunson’s scoring was central to that total, although the team result also depended on rebounding, free throws, turnovers, and contributions from the supporting cast.
How to evaluate a 37-point performance
A player’s point total is a useful starting point, but it is not a complete measure of efficiency.
For a fuller evaluation, analysts normally consider:
- Field goals made and attempted.
- Three-pointers made and attempted.
- Free throws made and attempted.
- Assists and turnovers.
- Minutes played and usage.
- Plus/minus, which measures a team’s net scoring margin while the player is on the court.
The supplied data confirms Brunson’s points, rebounds, and assists, but it does not provide his complete individual shooting line, minutes, or plus/minus. Those measures should not be guessed.
The strongest supported conclusion is that Brunson led the Knicks’ offense with 37 points and played a major part in the team’s victory.
Giannis Antetokounmpo’s Complete Statistical Performance
Giannis Antetokounmpo produced Milwaukee’s most comprehensive individual line. He led the Bucks in points, rebounds, and assists, demonstrating his influence across several areas of the game.
| Giannis Antetokounmpo’s recorded statistics | Total |
| Points | 30 |
| Rebounds | 15 |
| Assists | 8 |
Giannis recorded 30 points, 15 rebounds, and eight assists. Added together, those categories produce 53 points, rebounds, and assists, a simple counting-stat total rather than an official efficiency rating.
His performance shows that Milwaukee received substantial production from its leading player. The Bucks’ defeat cannot reasonably be explained as a game in which Giannis failed to contribute.
Scoring and playmaking
Giannis’s 30 points helped Milwaukee reach 109 as a team. His eight assists also indicate that he contributed to teammates’ scoring rather than relying exclusively on his own shots.
Assists do not capture every pass that helps create an opportunity, but they provide a useful record of direct passing contributions leading to made baskets.
Rebounding and possession control
Giannis’s 15 rebounds matched Hart’s total and led Milwaukee. Rebounding is particularly important when teams are shooting at different rates because it determines who gets possession after missed attempts.
Milwaukee collected 35 rebounds as a team, nine fewer than New York. Giannis’s individual total was strong, but the overall team comparison shows that the Bucks did not match New York’s collective rebounding output.
Why the result should not define the individual performance
A player can deliver excellent individual statistics and still be on the losing team. Basketball results depend on the combined performance of the lineup, the quality of the possessions created, and the opposition’s response.
Giannis’s 30 points, 15 rebounds, and eight assists demonstrate his individual production. The Knicks’ nine-point win demonstrates that New York performed better across the complete game.
Both conclusions can be true at the same time.
Josh Hart: 19 Points, 15 Rebounds and 7 Assists
Josh Hart’s performance is one of the clearest examples of all-around production in this matchup. He scored 19 points, collected 15 rebounds, and recorded seven assists.
| Josh Hart’s recorded statistics | Total |
| Points | 19 |
| Rebounds | 15 |
| Assists | 7 |
Hart’s combination of scoring, rebounding, and playmaking gave New York valuable contributions across three major categories.
Rebounding was Hart’s most notable contribution
Hart led the Knicks with 15 rebounds. That figure matched Giannis’s total and represented a substantial individual contribution to New York’s nine-rebound team advantage.
The team recorded 14 offensive rebounds and 30 defensive rebounds. Although the supplied data does not divide Hart’s individual rebounds into offensive and defensive categories, his total shows how active he was on the boards.
His passing supported team offense
Hart’s seven assists were the highest individual total listed for New York. The Knicks finished with 25 assists as a team, one more than Milwaukee.
A strong assist total can indicate that a player helped create scoring opportunities for teammates. It does not reveal every detail of decision-making, but it adds useful context to a performance that already included 19 points and 15 rebounds.
Why Hart’s performance matters
Hart did not need to lead the team in scoring to make a major contribution. His work on the boards and as a passer complemented Brunson’s scoring and helped New York maintain a balanced attack.
This is an important lesson when reading a box score: the player with the most points is not automatically the player who contributed in the greatest number of statistical areas.
Miles McBride and Mikal Bridges Add Scoring Support
New York’s supporting players made it harder for Milwaukee to focus its defensive attention on Brunson alone. Miles McBride scored 19 points, while Mikal Bridges added 14.
Miles McBride: 19 points
| Statistic | Total |
| Points | 19 |
| Rebounds | 2 |
| Assists | 1 |
McBride matched Hart’s scoring total and became another important source of offense for the Knicks.
His 19 points helped distribute the scoring load. When multiple players contribute meaningful totals, an offense can remain productive even when the leading scorer is not directly involved in every possession.
The supplied information does not include McBride’s shooting attempts or minutes played. Therefore, it is not possible to calculate his individual shooting efficiency or points per minute accurately from these figures alone.
Mikal Bridges: 14 points
| Statistic | Total |
| Points | 14 |
| Rebounds | 4 |
| Assists | 2 |
Bridges contributed 14 points, four rebounds, and two assists. His scoring added another layer to New York’s attack, while his rebounds and assists provided supplementary production.
The Knicks had four listed players score at least 14 points: Brunson, Hart, McBride, and Bridges. This distribution indicates that New York’s scoring was not concentrated entirely in one player.
Karl-Anthony Towns: 9 points and 10 rebounds
Towns recorded nine points, 10 rebounds, and four assists. His scoring total was lower than those of New York’s leading guards, but he reached double figures in rebounds and contributed as a passer.
| Statistic | Total |
| Points | 9 |
| Rebounds | 10 |
| Assists | 4 |
Towns’s 10 rebounds added to the Knicks’ overall advantage on the boards. His four assists also demonstrated a passing contribution that is not fully represented by his point total.
The supplied figures do not establish his complete defensive impact, screening effectiveness, or the number of shots he altered. Those aspects require more detailed game footage or tracking data.
Milwaukee’s Supporting Cast: AJ Green, Kyle Kuzma and Ryan Rollins
Although Giannis led Milwaukee, several other Bucks contributed meaningful scoring and playmaking. Their performances help explain how the team reached 109 points despite losing.
AJ Green: 18 points and six three-pointers
AJ Green scored 18 points and made six of his 12 field-goal attempts, all six of which were three-pointers according to the supplied data.
| Statistic | Total |
| Points | 18 |
| Field goals | 6/12 |
| Three-pointers | 6/12 |
| Three-point percentage | 50% |
Green’s outside shooting was one of Milwaukee’s most productive individual contributions. His six made three-pointers represented one-third of the Bucks’ 18 made threes.
That performance helps explain the team’s overall perimeter efficiency. Milwaukee converted 44% of its three-point attempts, compared with New York’s 41%.
However, Green’s shooting line alone does not show how the Knicks defended him, how many attempts came from particular locations, or what happened on possessions when he did not shoot.
Kyle Kuzma: 20 points off the bench
Kyle Kuzma recorded 20 points, four rebounds, and three assists. Among the listed Milwaukee bench players, he had the highest scoring total.
| Statistic | Total |
| Points | 20 |
| Rebounds | 4 |
| Assists | 3 |
Kuzma’s 20 points gave Milwaukee another substantial scoring source beyond Giannis. His four rebounds and three assists added to his contribution in other categories.
This performance is important when assessing the team result fairly. Milwaukee received strong production from several players, so the loss cannot be reduced to an absence of secondary scoring.
The broader issue was that New York generated more points overall through a combination of field goals, free throws, and possession advantages.
Ryan Rollins: 13 points and six assists
Rollins recorded 13 points, five rebounds, and six assists.
| Statistic | Total |
| Points | 13 |
| Rebounds | 5 |
| Assists | 6 |
His six assists were the second-highest individual total listed for Milwaukee after Giannis’s eight. Rollins also contributed five rebounds, providing support in more than one statistical category.
Together, Giannis and Rollins recorded 14 assists in their individual lines. Milwaukee finished with 24 team assists, indicating that other players also contributed to its passing game.
Myles Turner: 10 points and two blocks
Turner finished with 10 points, three rebounds, one assist, and two blocks.
His two blocks equaled New York’s total team blocks in the supplied data. Blocks are a useful defensive measure, but they do not capture every part of rim protection. A defender can affect a shot without blocking it, and positioning can influence an opponent’s decision before a shot is attempted.
Turner’s recorded line therefore provides evidence of a defensive contribution, but it is not enough to measure his entire defensive impact.
Other Milwaukee player statistics
| Player | Points | Rebounds | Assists |
| Giannis Antetokounmpo | 30 | 15 | 8 |
| Kyle Kuzma | 20 | 4 | 3 |
| AJ Green | 18 | Not supplied | Not supplied |
| Ryan Rollins | 13 | 5 | 6 |
| Myles Turner | 10 | 3 | 1 |
| Cole Anthony | 7 | Not supplied | 2 |
| Gary Harris | 5 | Not supplied | Not supplied |
| Gary Trent Jr. | 3 | 0 | 1 |
| Bobby Portis | 3 | 3 | 2 |
The table includes only the figures available in the supplied data. Missing rebound and assist totals have not been estimated.
Milwaukee’s scoring distribution shows that several players made meaningful contributions. Its defeat was more closely connected to the overall statistical balance than to a complete failure by its supporting cast.
Knicks Bench Statistics and Their Contribution
New York received additional production from Mitchell Robinson, Jordan Clarkson, Tyler Kolek, and Guerschon Yabusele. Their scoring totals were smaller than those of the starters, but their contributions help complete the picture of the Knicks’ performance.
| Knicks bench player | Points | Rebounds | Assists |
| Mitchell Robinson | 6 | 7 | 1 |
| Jordan Clarkson | 6 | 4 | 3 |
| Tyler Kolek | 5 | Not supplied | Not supplied |
| Guerschon Yabusele | 3 | 1 | 1 |
Mitchell Robinson’s rebounding
Robinson scored six points and recorded seven rebounds. His rebounding total was particularly useful in the context of New York’s overall advantage on the boards.
The Knicks finished with 44 rebounds, including 14 offensive rebounds. Robinson’s seven rebounds added another source of possession recovery alongside Hart and Towns.
Jordan Clarkson’s balanced contribution
Clarkson recorded six points, four rebounds, and three assists. His statistics show a contribution across scoring, rebounding, and passing.
The assist total is especially useful context because it demonstrates that New York’s playmaking was not limited to its leading starters. However, the available data does not establish exactly how many points the bench generated as a group relative to Milwaukee’s bench.
Additional scoring from Tyler Kolek and Guerschon Yabusele
Kolek contributed five points, while Yabusele recorded three points, one rebound, and one assist.
Their point totals were modest, but every contribution formed part of the team’s final production. Without complete minutes and possession data, it would be inappropriate to assign a precise efficiency rating to either player.
The available figures support a straightforward conclusion: New York received scoring and rebounding from multiple players, which complemented its leading performers.
Why New York Won Despite Milwaukee’s Better Shooting
The most revealing part of the game is the contrast between Milwaukee’s shooting efficiency and New York’s overall scoring advantage.
The Bucks shot 52% from the field and 44% from three-point range. The Knicks shot 45% from the field and 41% from three-point range. On those measures, Milwaukee was more accurate.
Yet New York won by nine points. The explanation becomes clearer when the other statistical categories are considered together.
Free throws: An 11-point advantage
New York made 28 free throws, while Milwaukee made 17. That created an 11-point difference in free-throw scoring.
The Knicks also attempted eight more free throws. Their 33 attempts produced 28 points, while Milwaukee’s 25 attempts produced 17.
Free throws can make a major difference when field-goal percentages favor the opposing team. They provide scoring opportunities that do not require a made field goal and can help a team maintain its total when outside shots are not falling as often.
The supplied figures establish the difference in free-throw production, although they do not identify every foul or possession that led to those attempts.
Offensive rebounds: More chances to score
New York collected 14 offensive rebounds, while Milwaukee recorded five.
An offensive rebound allows a team to retain possession after a missed field-goal attempt. That can create another opportunity to score without needing to regain possession through a defensive stop.
The Knicks attempted 84 field goals, compared with 71 for the Bucks. New York therefore attempted 13 more shots from the field, even though it made only one additional field goal.
The offensive-rebound advantage is an important part of understanding that difference. More attempts can help compensate for a lower conversion rate, provided those additional opportunities produce enough points.
Turnovers: Better ball security
The Knicks committed 12 turnovers, compared with Milwaukee’s 15.
A turnover ends a possession without a successful field-goal attempt. Limiting turnovers can help a team preserve scoring opportunities, particularly against an opponent that shoots efficiently.
New York’s three-turnover advantage was not enormous, but it supported the team’s wider possession advantage.
A combined explanation
No single statistic completely explains the result. The more useful approach is to consider the numbers together:
- Milwaukee converted field-goal attempts more efficiently.
- New York generated 13 more field-goal attempts.
- The Knicks made 11 more free throws.
- New York collected nine more rebounds.
- Milwaukee committed three more turnovers.
These differences help explain why the Knicks scored 118 points despite shooting a lower percentage from the field.
How to Read Basketball Player Statistics Correctly
A box score is useful because it provides a quick summary of what happened in a game. However, understanding the numbers requires more than identifying the highest point total.
Points measure scoring, not total impact
Brunson’s 37 points made him New York’s leading scorer. Giannis’s 30 points led Milwaukee.
Those numbers provide a clear comparison of scoring output, but they do not fully measure defense, passing decisions, screens, spacing, or other contributions.
A player with fewer points may still have influenced the game through rebounding, assists, or defensive work.
Rebounds must be considered alongside team totals
Hart and Giannis each recorded 15 rebounds. Yet New York won the overall rebounding battle 44-35.
This comparison demonstrates why individual and team statistics should be read together. A player’s total tells us about his contribution, while the team total reveals whether the lineup as a whole secured more possessions.
Shooting percentage does not measure scoring volume
Milwaukee’s 52% field-goal percentage was better than New York’s 45%. However, New York attempted 84 field goals compared with Milwaukee’s 71.
The difference in attempts matters because percentage describes the share of attempts converted, not the total number of scoring opportunities.
For a deeper analysis, readers can also consider effective field-goal percentage, which accounts for the extra value of three-pointers, and true shooting percentage, which incorporates field goals, three-pointers, and free throws.
These measures offer a broader view of scoring efficiency. Calculating accurate player-level figures would require complete individual shooting and free-throw data, which is not provided for every player in the supplied information.
Assists provide context about ball movement
New York recorded 25 assists and Milwaukee recorded 24. The difference was small, so it would be misleading to claim that passing volume alone explains the result.
The Knicks’ assist total does, however, show that their scoring was accompanied by substantial recorded passing contributions.
Turnovers and rebounds help explain possession value
A team can score efficiently on individual attempts but still lose if it gives the opponent more opportunities to score.
Offensive rebounds can extend possessions, while turnovers can end them prematurely. Reading these categories alongside shooting statistics provides a more complete understanding of team performance.
Historical Context and Season Matchup Information
The supplied season matchup summary lists three meetings between Milwaukee and New York:
| Listed matchup | Result |
| October 29, 2025 | Milwaukee Bucks 121, New York Knicks 111 |
| November 29, 2025 | New York Knicks 118, Milwaukee Bucks 109 |
| February 28, 2026 | New York Knicks 127, Milwaukee Bucks 98 |
The first listed meeting favored Milwaukee by 10 points. New York then won the November 29 game by nine points and the February 28 game by 29 points.
Based on these three supplied results, the Knicks won two of the three listed meetings, while Milwaukee won one. The combined scoring totals across those games were 356 points for New York and 328 for Milwaukee.
This historical comparison provides additional context, but it should not be confused with a complete season record or a claim about playoff outcomes. It simply summarizes the three matchups listed in the supplied data.
The different margins also demonstrate why each game deserves its own statistical analysis. A team can win one meeting through different strengths than it uses in another, and individual performances can change significantly from game to game.
Official Box Score and Statistical Verification
Readers looking to verify the final score, individual statistics, and recorded team totals can consult the ESPN box score for the November 29, 2025, game.
The official box score is the appropriate starting point for checking recorded points, rebounds, assists, shooting figures, and the final result. More detailed play-by-play information can help explain when scoring runs occurred or how a particular stretch influenced the game.
A useful distinction is the difference between recorded data and interpretation. The final score, shooting totals, and listed player statistics are data points. Explanations of why a team won are interpretations that should be grounded in those points.
For example, it is accurate to say that New York made 11 more free throws and collected nine more rebounds. It is reasonable to identify those advantages as important factors in the victory. It would be less reliable to claim that a particular unprovided defensive adjustment caused the result without additional evidence.
Frequently Asked Questions
1. Who won the Knicks vs Milwaukee Bucks game on November 29, 2025?
The New York Knicks defeated the Milwaukee Bucks 118-109 at Madison Square Garden during NBA Cup Group Play.
2. How many points did Jalen Brunson score against Milwaukee?
Jalen Brunson scored 37 points, leading the Knicks and all listed players in scoring for the game.
3. What were Giannis Antetokounmpo’s statistics?
Giannis recorded 30 points, 15 rebounds, and eight assists. He led Milwaukee in all three categories according to the supplied statistics.
4. Which team had more rebounds?
New York collected 44 rebounds, compared with Milwaukee’s 35. The Knicks also recorded 14 offensive rebounds, while the Bucks had five.
5. Why did the Knicks win despite shooting a lower percentage?
New York made 11 more free throws, collected nine more rebounds, and committed three fewer turnovers. These advantages helped offset Milwaukee’s better field-goal and three-point percentages.
6. Who were Milwaukee’s leading supporting scorers?
Kyle Kuzma scored 20 points, AJ Green added 18, and Ryan Rollins recorded 13. Their performances supported Giannis Antetokounmpo’s 30-point effort.
Conclusion
The November 29, 2025, meeting between the New York Knicks and Milwaukee Bucks was a strong example of how basketball games are decided by more than shooting percentages. New York won 118-109 by combining high-level individual scoring with better rebounding, more successful free throws, and fewer turnovers.
Jalen Brunson led the Knicks with 37 points, while Josh Hart contributed 19 points, 15 rebounds, and seven assists. Miles McBride added 19 points, and Karl-Anthony Towns recorded 10 rebounds and four assists. These contributions helped New York recover from Milwaukee’s strong first quarter and outscore the Bucks in each of the final three periods.
Giannis Antetokounmpo delivered Milwaukee’s most complete individual performance with 30 points, 15 rebounds, and eight assists. Kyle Kuzma scored 20 points, and AJ Green made six three-pointers. Milwaukee’s 52% field-goal shooting and 18 made threes demonstrated its offensive efficiency, but those strengths were outweighed by New York’s advantages in other areas.
The central lesson from the game is that shooting accuracy, possession control, rebounding, and free-throw production must be considered together. The final score records the outcome, while the individual and team statistics explain the different ways both teams contributed to it.
